Tool Configurations: The Secret Sauce for Agent Customization

Introduction: Beyond Basic Tool Integration

Building intelligent agents in Vectara involves three key components that work together to create powerful automation:

Tool Servers are external services that expose various capabilities through the Model Context Protocol (MCP). These might include web search services, database connectors, API integrations, or custom business logic. When you register tool servers with Vectara, they expose a collection of tools that become available platform-wide.

Agents are AI-powered entities that can understand natural language, reason about problems, and take actions using available tools. When you create an agent in Vectara, you define exactly which tools your agent can use through tool configurations.

Tool Configurations serve a dual purpose: they both select which tools from the platform-wide list of available tools your agent can access AND define how those tools should behave. Each configuration specifies a particular tool (like a specific tool from an MCP server or a built-in capability like web search) while also controlling its behavior through argument overrides. Your agent only has access to tools through these configurations - it cannot use raw tools directly.

This deep dive explores how Vectara's tool configurations transform basic tools into precisely tailored instruments that work exactly how you need them to.

Understanding Tool Configurations

The Tool Configuration Architecture

Every agent contains a tool_configurations map where each key represents a named configuration that your agent can use:

Critical Understanding: The LLM sees and uses the configuration name (like customer_search), not the underlying tool name. When your agent decides to search for information, it will choose to call customer_search - so this name must clearly describe what the configuration does and when to use it.

What Makes Tool Configurations Special?

Tool configurations act as a customization layer between your agent and the actual tools, giving you granular control over how tools behave. Instead of letting the LLM fill in all tool parameters dynamically, you can:

• Lock down critical parameters that should never change
• Pre-populate fields with business-specific values
• Create multiple variants of the same tool for different use cases
• Inject dynamic context from session or agent metadata

You can configure the same underlying tool multiple times with different configuration names and different settings. For example, you could create both quick_search and deep_search configurations that both use the web search tool but with different limits and timeouts. Your agent will see these as two distinct tools it can choose from, allowing it to pick the right search approach for different situations.

Types of Tool Configurations

Every tool configuration has the same basic structure but varies by the type of tool it's configuring:

1. Vectara Built-in Tools

Vectara provides two built-in tool types that are commonly used:

Web Search Tool Configurations

Corpora Search Tool Configurations

2. MCP Tool Configurations

For complete configuration options and all available parameters for tool configurations, see the tool_configurations parameter in the Create Agent API documentation.

Argument Overrides: Controlling Tool Behavior

What Are Argument Overrides?

Argument overrides are the heart of tool configurations - they're predefined values that replace or supplement the parameters that an LLM would normally fill in when calling a tool. Think of them as "hardcoded settings" that give you precise control over tool behavior.

Without argument overrides, when your agent uses a web search tool:

• The LLM decides the search query
• The LLM chooses how many results to return
• The LLM picks the search provider
• The LLM sets all other parameters

With argument overrides, you can:

• Lock down the number of results to exactly 5
• Force the use of a specific search provider
• Pre-populate certain fields while letting the LLM fill others
• Inject dynamic values from your session or agent context

The Control Spectrum

Argument overrides give you a spectrum of control:

• Full LLM Control: No overrides - LLM fills all parameters
• Partial Control: Override some parameters, let LLM handle others
• Full Control: Override all parameters for completely predictable behavior

How to Configure Argument Overrides

Static Value Overrides

Static overrides allow you to hardcode specific parameter values that remain constant across all tool calls. These are useful for setting operational constraints, default behaviors, or ensuring consistent configuration.

Dynamic Context Integration

Dynamic overrides use reference syntax to pull values from your session or agent metadata at runtime. This allows for personalized, context-aware tool behavior without hardcoding values.

Dynamic References:

You can mix static and dynamic overrides within the same configuration - some parameters can be hardcoded static values while others pull from dynamic context, giving you maximum flexibility in tool behavior.

Available Context Paths:

• session.metadata.* — Access any session metadata field
• agent.metadata.* — Access any agent metadata field

All references must be valid JSONPath expressions that resolve to a value in your session or agent metadata. This allows you to access nested objects, array elements, and complex data structures:

Troubleshooting Common Issues

Configuration Not Working

• Verify tool configuration names match exactly in your agent definition
• Check that argument override keys match the tool's input schema
• Ensure dynamic references point to existing metadata fields

Dynamic References Failing

• Confirm metadata exists at session creation or agent configuration
• Verify the dot notation path is correct (session.metadata.field_name)
• Check for typos in reference paths

Tool Behavior Unexpected

• Review which parameters are overridden vs. LLM-controlled
• Test with different argument override combinations
• Validate that query configurations align with your corpus setup

Conclusion: Mastering Tool Configuration

Tool configurations are the key to building production-ready agents that behave predictably and securely. By mastering argument overrides, dynamic context integration, and configuration patterns, you can create agents that are both powerful and precisely controlled.

For engineers, this means you don’t have to choose between flexibility and reliability—you get both. With Vectara, you can set hard guarantees where predictability is critical, inject contextual values for personalization, and reuse the same underlying tools across multiple workflows without duplicating effort. That balance is what makes tool configurations such a powerful engineering primitive.

The combination of static overrides for operational constraints, dynamic references for personalization, and multiple configurations for flexibility gives you unprecedented control over how your agents interact with tools. Start with simple static overrides, then gradually incorporate dynamic context as your use cases become more sophisticated.

Remember: every argument you override is one less decision point for the LLM, leading to more predictable and reliable agent behavior in production environments. That’s why we built Vectara’s tooling with engineers in mind—to give you precision, safety, and scalability without sacrificing speed of development.

If you’re ready to take agent customization to the next level, reach out to us to learn more

Learn more about Vectara Agents here: https://www.vectara.com/blog/announcing-vectara-agents-enterprise-ai-that-works